Technical Business Analyst

Get Covered is a fast-moving post-acquisition startup focused on providing cost-effective coverage solutions. The Technical Business Analyst role involves optimizing context for AI-generated tickets, maintaining accurate documentation, and ensuring that product specifications align with reality to support product managers and engineers.

Responsibilities:

• Understand and write down how the platform actually behaves today - the workflows, the exception paths, the rules, and the undocumented behavior currently living in people's heads
• Build and maintain the reference material that our AI tooling and our engineers pull from, and keep it accurate as the product changes. Stale documentation now produces bad tickets and bad code automatically, at scale
• Review tickets and specs against reality before anyone builds them. This is the part that matters most: AI-generated work is confidently wrong exactly where it costs the most - edge cases, compliance rules, customer-specific commitments, anything that is not in the repo or the training data
• Capture acceptance criteria, edge cases, failure behavior, and explicit non-goals so a pod can pick something up and build it without a meeting

Requirements:

• 3+ years as a business analyst, technical analyst, product analyst, data analyst, or in product operations, working closely with engineers
• Strong SQL. You write your own queries against a real schema, you understand what a join is doing to your row count, and you sanity-check your results before presenting them
• You can read a database schema and work out how a product behaves from it
• You already work with AI as a daily tool, not an experiment. You know how to structure context so output is reliable, you iterate on prompts rather than accepting the first answer, and you know when a model is confidently wrong and you check
• You can build a rough working thing with AI assistance. Not production code. A prototype good enough that people can react to it instead of imagining it
• You write clearly. In a setup like ours, written clarity is not a soft skill. It is the input that determines what gets built
• Analytical honesty. You quantify rather than characterize, you name your assumptions, and when numbers don't reconcile you stop and investigate instead of shipping the chart
• Comfort operating without process scaffolding, and comfort saying 'not this week, here's why' when three people want the same hour
• B2B SaaS with enterprise customers
• compliance- or workflow-heavy products
• Python for analysis
• experience maintaining documentation that AI tooling depends on